Category Archives: Uncategorized

Abstract-The design and development of a drone for spraying pesticides on agricultural lands have been described in this paper. The drone developed is a quadcopter integrated with a spraying mechanism. A quadcopter can be described as a mechanical device that can hover using propellers fitted into it is four arms. Hovering is achieved using one set of clockwise spinning propellers and another set of counter- clockwise spinning propellers that generate the thrust required to facilitate the taking off and hovering process. The agricultural industry contributes heavily to India’s GDP, thus making it one of the chief sources of revenue. It is the foundation of India’s economy and contributes to approximately one-fourth of its gross domestic product. It is inevitable that fertilizers and pesticides will be used to increase crop yields. However, few health-related problems can arise due to prolonged exposure to such chemicals during manual spraying. A few examples include mild skin irritation to congenital disabilities, changes in genetics, falling into a coma, or even death in severe cases. Drones have been used extensively in agriculture over the past few years. This paper describes the components required for the successful design and development of a quadcopter that can be utilized for spraying fertilizer on agricultural lands. The quadcopter is equipped with a container carrying a Direct Current water pump fitted with a pipe and nozzle arrangement. The liquid passes and is controlled using the instructions that the user provides the controller.

Abstract-Ransomware attacks have escalated, posing significant threats to organizations by encrypting critical data and demanding ransoms. Traditional security measures often fall short against sophisticated ransomware variants. This paper explores the deployment of hardware-based honeypot files utilizing Server Message Block (SMB) traps as a proactive defense mechanism. By integrating deceptive SMB shares at the hardware level, organizations can detect, analyze, and mitigate ransomware activities more effectively.

Abstract-In the era of advanced artificial intelligence and machine learning, collaborative deep learning has emerged as a powerful approach to leverage distributed data and computational resources. However, a significant challenge that persists is ensuring the generalizability of models developed in collaborative environments. This project addresses the generalizability challenge in collaborative deep learning by proposing a novel framework that integrates advanced techniques in model training and validation. Deep learning models typically require data to be collected at a centralized location to learn effective representations, which introduces several issues such as communication costs and risks to data privacy. These issues are particularly critical in the case of clinical data, where patient privacy is paramount. In such contexts, distributed machine learning offers a viable solution where various data-holding sites can locally train a mutually agreed-upon model and share their knowledge. Federated learning (FL) facilitates this process using a client-server framework. Clients in the FL environment are independent small edge devices that retain their data locally, while the server acts as a central site that aggregates and distributes the knowledge learned by each client to others. The server receives locally trained weights from all participating clients, aggregates them, and then transfers the aggregated weights back to all clients before the next training round begins. This iterative process continues until the server achieves the desired accuracy. FL thus enables multiple clients to collaboratively train a shared global model without sharing their local data, preserving data privacy and addressing issues of limited data availability. However, FL faces challenges such as high communication costs for transferring weights, statistical data heterogeneity among clients, and the single point of failure of the server. Client heterogeneity arises mainly due to differences in data distribution among clients and their respective computational power. This project targets statistical data heterogeneity in the FL environment and proposes a simple yet effective attention-based approach to address this issue. Specifically, in the proposed setting, each client sends a mean representation to the centralized server along with the trained model’s weights. A similarity matrix is computed based on the similarity score of each client’s mean representation from every other participating client. This similarity matrix determines the weightage of each client’s model in the aggregated model. The centralized server computes the attention vector for each client using this similarity matrix and then broadcasts this attention vector to all clients. This attention mechanism is implemented both on the centralized server and the participating clients. We consider FedAvg, FedProx, and FedMomentum as baselines for comparison, and our proposed approach outperforms all of them. For statistical heterogeneity, we perform extensive experiments on FOOD101 and CIFAR10, demonstrating that our approachperforms well even with highly skewed data. To address the single point of failure issue in FL, we propose an efficient version of swarm learning. We demonstrate the effectiveness of context- aware swarm learning through experiments on the HAM10000 and ISIC Skin Lesion 2019 datasets. Additionally, to mitigate the high communication costs in FL, we propose BAFL (Federated Learning for Base Ablation), which introduces a fine-tuning approach to leverage the feature extraction ability of layers at different depths of deep neural networks. We evaluate the proposed approach using VGG-16 and ResNet-50 models on datasets including WBC, FOOD-101, and CIFAR-10, achieving up to two orders of magnitude reduction in total communication cost compared to conventional federated learning.

Abstract-Muslim-run media outlets influence India’s online conversation by highlighting underrepresented voices, fighting false information, and encouraging open discussions. In India, the mainstream media is often accused of misleading or ignoring Muslim viewpoints. As a result, independent digital platforms created by and for Muslims have become important for sharing their stories, supporting their rights, and shaping their narratives. Independent internet platforms like TwoCircles.net and Maktoob Media are crucial spaces for representation, advocacy, and grassroots storytelling in India, while mainstream media have been condemned for reinforcing negative stereotypes and marginalizing Muslim voices. This study emphasizes the importance of editorial independence in unbiased reporting and helps us understand how independent Muslim media work in India’s changing digital ecosystem and how they democratize media representation and promote public equity.

Abstract-This study examines the impact of key macroeconomic indicators—Consumer Price Index for All Urban Consumers (CPI-U) and Federal Reserve Rate (Fed Rate)—on the performance of Bitcoin (BTC), Gold (XAUUSD), and the S&P500. Through regression analysis, the research provides a comparative perspective on traditional and emerging asset classes (Wu, 2022). The findings indicate that inflation plays a dominant role in influencing asset prices, with the strongest effects observed in equities and Gold. Bitcoin, despite its perception as a digital hedge, exhibits moderate sensitivity to inflation alongside high volatility driven by speculative and external factors. The Fed Rate has a weaker influence on all three assets, particularly Bitcoin, suggesting that monetary policy alone does not dictate cryptocurrency price movements (Pinchuk, 2021). The study underscores the importance of inflation in shaping investment strategies, especially for traditional assets, while highlighting Bitcoin’s speculative nature. The research also introduces a model framework that can be adapted to assess various asset classes against different macroeconomic indicators. Future work should explore advanced analytical techniques and a broader set of variables to enhance market insights.

Abstract-The Hostel Management System (HMS) is an automated solution designed to streamline hostel operations, including student registration, room allocation, mess management, and attendance tracking. This system enhances efficiency, reduces manual workload, and ensures data security and accessibility. This paper presents an overview of the proposed system, its architecture, implementation, advantages, and future scope.For room allocation, Genetic Algorithm is used which allocates room to the students as per their preferences. Also, the web application consists of a generation of barcodes which can be used by the students to scan it while leaving/entering hostel premises. And the same can be used in mess also. Students will get endorsement notices in their mails which informs guardians about their ward’s presence in the hostel and their curricula using this model just in one touch. The student can raise leave requests as well as raise cleaning issues to the warden. The warden can monitor the student records and daily roll call list. The fee details and the due of the student can also be verified using this QR database management and inquiry method.

Abstract-This paper will design an Automatic Chakali Making Machine based on Programmable Logic Controller (PLC) technology to automate the traditional chakali making process. Automation is a major concern in contemporary food industries to overcome the limitations of quality control, production rate, shortage of manpower and profitability. The suggested system combines mechanical, electrical and control elements to execute primary operations such as dough extrusion, shaping, cutting and frying with high accuracy and efficiency. The process starts with a dough feeder, which transports the dough to an extruder, where PLC controls the extrusion process to deliver regular shape and size. Uniformity is achieved by a synchronized cutting system and the shaped chakalis are transported to a frying unit by a conveyor system, where PLC automation controls temperature and oil levels to deliver uniform cooking. The system also features real-time monitoring to deliver safety and efficiency. With increasing demand for food industry automation, manufacturers are continuously upgrading equipment to meet consumer demands, deliver hygiene standards and boost profitability. By minimizing manual intervention, delivering optimal utilization of ingredients and product uniformity, this automated system not only increases productivity and food safety but also enables small to medium-scale businesses to boost production on a large scale in an efficient manner. This project is intended to revolutionize chakali manufacturing by introducing automation, enhancing raw material traceability and delivering consistency in mass production.

Abstract-C. Gowrishankar, S.Girieshwaran, M.Keerthivarman, C.NaveenThis project focuses on improving the cart’s utility by integrating advanced loading and storage features. A cylindrical roller mechanism is introduced to simplify the process of loading and unloading items, reducing the need for manual effort and improving efficiency. The inclusion of two spacious and organized compartments provides ample storage space, ensuring the safe and secure transportation of stationary items. Attention is given to the ergonomic design of these compartments to facilitate easy access and optimal space utilization. Additionally, this stage involves analysing the structural stability of the cart to ensure it can handle varying weights without compromising performance. By enhancing its functional capabilities, this phase ensures the cart is tailored to meet the material handling needs of a busy campus environment.

Abstract-There was much hype and importance of the Year 2000 as known as Y2K Problem and all the legacy application Software needs to changed and incorporated with This and now we talk about IOT – Internet of Things that is Network of Physical Objects that can be connected and share data within themselves. So these changes are like Paradigm changes and it impacted a lot in our daily life, this article will talk about more About on this in details.